An audio signal of 10s length is sampled at 16kHz and converted into a single channel by averaging all channels. The log-melspectrogram corresponding to the audio has a size (64 \(\times \)  313). This gives a total of 309 contextual frames using a context window of 5 with unit stride as explained in Section REF . Under these settings, the training dataset consists of 92700-examples ( 92700= 309 \(\times \)  300 ) each of 320-dimension. AE-model is trained using Adam optimizer [1]} for 5k epochs using mean square error as a loss function.
